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Record W2972269804 · doi:10.1017/dmp.2019.81

Attitudes of Medical Students Toward Volunteering in Emergency Situations

2019· article· en· W2972269804 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDisaster Medicine and Public Health Preparedness · 2019
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAltruism (biology)Health careDisaster medicineNatural disasterMedical careMedicinePsychologyMedical emergencyFamily medicineNursingSuicide preventionPoison controlSocial psychologyPolitical scienceGeography

Abstract

fetched live from OpenAlex

OBJECTIVE: With the rising incidence of health care emergencies, there has been a considerable burden placed on health care systems worldwide. We aimed to determine the willingness and capacity of medical students in Ireland to volunteer during health care emergencies. METHODS: An online, cross-sectional survey of medical students at the National University of Ireland was conducted in 2015. RESULTS: Respondents totaling 274 completed the survey (response rate - 30.1%). Of participants, 69.0% were willing to volunteer in the event of a natural disaster and 59.1% in an event of an infectious epidemic, with altruism being the strongest motivational factor. Only a minority of students (23.7%) felt their current skill level would be useful in an emergency setting. CONCLUSIONS: Medical students express a strong interest in actively participating during health care emergencies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.135
GPT teacher head0.491
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it